Implementing a Commercial-Strength Parallel Hybrid Movie Recommendation Engine

Author

Amolochitis, Emmanouil ; Christou, Ioannis T. ; Zheng-Hua Tan

Volume

29

Issue

2

fYear

2014

fDate

Mar.-Apr. 2014

Firstpage

92

Lastpage

96

Abstract

AMORE is a hybrid recommendation system that provides movie recommendations for a major triple-play services provider in Greece. Combined with our own implementations of several user-, item-, and content-based recommendation algorithms, AMORE significantly outperforms other state-of-the-art implementations both in solution quality and response time. AMORE currently serves daily recommendation requests for all active subscribers of the provider´s video-on-demand services and has contributed to an increase of rental profits and customer retention.

Keywords

content-based retrieval; customer services; recommender systems; video on demand; AMORE; commercial-strength parallel hybrid movie recommendation engine; content-based recommendation algorithm; customer retention; daily recommendation request; hybrid recommendation system; item-based recommendation algorithm; rental profits; response time; solution quality; triple-play services provider; user-based recommendation algorithm; video-on-demand services; Databases; Educational institutions; History; Measurement; Motion pictures; Recommender systems; Time factors; information filtering; information search and retrieval; intelligent systems; pattern recognition; recommender systems;

fLanguage

English

Journal_Title

Intelligent Systems, IEEE

Publisher

ieee

ISSN

1541-1672

Type

jour

DOI

10.1109/MIS.2014.23

Filename

6832879